from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 1.994884 | 0.172649 | NaN | 0.000401 | 0.001995 | brute | -1 | 1 | 0.663 | 0.200178 | 0.006385 | 0.687 | 9.965554 | 9.970623 |
| 4 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.951273 | 0.047169 | NaN | 0.000271 | 0.002951 | brute | -1 | 5 | 0.757 | 0.208435 | 0.008071 | 0.742 | 14.159178 | 14.169788 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.199261 | 0.025263 | NaN | 0.000364 | 0.002199 | brute | 1 | 100 | 0.882 | 0.254386 | 0.009528 | 0.875 | 8.645381 | 8.651443 |
| 8 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.020690 | 0.001177 | NaN | 0.000039 | 0.020690 | brute | 1 | 100 | 1.000 | 0.010163 | 0.001924 | 0.000 | 2.035822 | 2.071966 |
| 10 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.924734 | 0.059220 | NaN | 0.000274 | 0.002925 | brute | -1 | 100 | 0.882 | 0.252963 | 0.010147 | 0.875 | 11.561900 | 11.571198 |
| 11 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.027676 | 0.005492 | NaN | 0.000029 | 0.027676 | brute | -1 | 100 | 1.000 | 0.009000 | 0.001279 | 0.000 | 3.074985 | 3.105884 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.188334 | 0.040193 | NaN | 0.000366 | 0.002188 | brute | 1 | 5 | 0.757 | 0.206100 | 0.009081 | 0.742 | 10.617819 | 10.628121 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 1.223682 | 0.020244 | NaN | 0.000654 | 0.001224 | brute | 1 | 1 | 0.663 | 0.204675 | 0.011459 | 0.687 | 5.978645 | 5.988009 |
| 19 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.747191 | 0.032236 | NaN | 0.000009 | 0.001747 | brute | -1 | 1 | 0.896 | 0.031046 | 0.001858 | 0.967 | 56.277871 | 56.378567 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 2.764815 | 0.041363 | NaN | 0.000006 | 0.002765 | brute | -1 | 5 | 0.922 | 0.033079 | 0.001158 | 0.974 | 83.581296 | 83.632454 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 2.132174 | 0.070030 | NaN | 0.000008 | 0.002132 | brute | 1 | 100 | 0.929 | 0.075151 | 0.002130 | 0.975 | 28.371885 | 28.383277 |
| 28 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 2.782344 | 0.052769 | NaN | 0.000006 | 0.002782 | brute | -1 | 100 | 0.929 | 0.075194 | 0.003862 | 0.975 | 37.002119 | 37.050903 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 2.130075 | 0.029014 | NaN | 0.000008 | 0.002130 | brute | 1 | 5 | 0.922 | 0.031093 | 0.002596 | 0.974 | 68.506535 | 68.744841 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.072366 | 0.010114 | NaN | 0.000015 | 0.001072 | brute | 1 | 1 | 0.896 | 0.030933 | 0.002092 | 0.967 | 34.667306 | 34.746517 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.578 | 0.0 | -1 | 1 | 0.051 | 0.005 | 0.240 | 0.241 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.768 | 0.0 | -1 | 5 | 0.050 | 0.001 | 0.236 | 0.236 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.941 | 0.0 | 1 | 100 | 0.049 | 0.002 | 0.237 | 0.237 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.794 | 0.0 | -1 | 100 | 0.055 | 0.006 | 0.214 | 0.215 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | 6.791 | 0.0 | 1 | 5 | 0.051 | 0.002 | 0.232 | 0.232 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | 6.778 | 0.0 | 1 | 1 | 0.050 | 0.001 | 0.236 | 0.236 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.326 | 0.0 | -1 | 1 | 0.010 | 0.001 | 0.506 | 0.507 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.315 | 0.0 | -1 | 5 | 0.011 | 0.002 | 0.470 | 0.480 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.305 | 0.0 | 1 | 100 | 0.010 | 0.001 | 0.527 | 0.528 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.334 | 0.0 | -1 | 100 | 0.009 | 0.000 | 0.509 | 0.510 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.322 | 0.0 | 1 | 5 | 0.009 | 0.002 | 0.524 | 0.532 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.324 | 0.0 | 1 | 1 | 0.009 | 0.001 | 0.567 | 0.568 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.995 | 0.173 | 0.000 | 0.002 | -1 | 1 | 0.200 | 0.006 | 9.966 | 9.971 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.002 | 0.000 | 0.023 | -1 | 1 | 0.008 | 0.000 | 2.728 | 2.730 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.951 | 0.047 | 0.000 | 0.003 | -1 | 5 | 0.208 | 0.008 | 14.159 | 14.170 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.003 | 0.000 | 0.025 | -1 | 5 | 0.009 | 0.001 | 2.966 | 2.977 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.199 | 0.025 | 0.000 | 0.002 | 1 | 100 | 0.254 | 0.010 | 8.645 | 8.651 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.001 | 0.000 | 0.021 | 1 | 100 | 0.010 | 0.002 | 2.036 | 2.072 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.925 | 0.059 | 0.000 | 0.003 | -1 | 100 | 0.253 | 0.010 | 11.562 | 11.571 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.005 | 0.000 | 0.028 | -1 | 100 | 0.009 | 0.001 | 3.075 | 3.106 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.188 | 0.040 | 0.000 | 0.002 | 1 | 5 | 0.206 | 0.009 | 10.618 | 10.628 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.001 | 0.000 | 0.021 | 1 | 5 | 0.008 | 0.000 | 2.541 | 2.543 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.224 | 0.020 | 0.001 | 0.001 | 1 | 1 | 0.205 | 0.011 | 5.979 | 5.988 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.002 | 0.000 | 0.021 | 1 | 1 | 0.008 | 0.001 | 2.480 | 2.502 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.747 | 0.032 | 0.000 | 0.002 | -1 | 1 | 0.031 | 0.002 | 56.278 | 56.379 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.003 | 0.000 | 0.005 | -1 | 1 | 0.001 | 0.000 | 6.086 | 6.290 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.765 | 0.041 | 0.000 | 0.003 | -1 | 5 | 0.033 | 0.001 | 83.581 | 83.632 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.005 | 0.000 | 0.007 | -1 | 5 | 0.001 | 0.000 | 9.223 | 9.357 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.132 | 0.070 | 0.000 | 0.002 | 1 | 100 | 0.075 | 0.002 | 28.372 | 28.383 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 3.849 | 3.872 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.782 | 0.053 | 0.000 | 0.003 | -1 | 100 | 0.075 | 0.004 | 37.002 | 37.051 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.004 | 0.000 | 0.007 | -1 | 100 | 0.001 | 0.000 | 9.114 | 9.171 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.130 | 0.029 | 0.000 | 0.002 | 1 | 5 | 0.031 | 0.003 | 68.507 | 68.745 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 4.435 | 4.491 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.072 | 0.010 | 0.000 | 0.001 | 1 | 1 | 0.031 | 0.002 | 34.667 | 34.747 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.723 | 2.742 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.891720 | 1.171892 | NaN | 0.000090 | 0.000892 | kd_tree | -1 | 1 | 0.929 | 0.113312 | 0.004687 | 0.910 | 7.869611 | 7.876342 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.141847 | 0.397180 | NaN | 0.000070 | 0.001142 | kd_tree | -1 | 5 | 0.946 | 0.196773 | 0.002756 | 0.941 | 5.802866 | 5.803435 |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 5.498338 | 0.533157 | NaN | 0.000015 | 0.005498 | kd_tree | 1 | 100 | 0.951 | 0.594319 | 0.007156 | 0.940 | 9.251497 | 9.252167 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 3.021899 | 0.291408 | NaN | 0.000026 | 0.003022 | kd_tree | -1 | 100 | 0.951 | 0.568129 | 0.010698 | 0.940 | 5.319035 | 5.319978 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.672402 | 0.245720 | NaN | 0.000048 | 0.001672 | kd_tree | 1 | 5 | 0.946 | 0.194308 | 0.005913 | 0.941 | 8.606966 | 8.610950 |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.904323 | 0.193756 | NaN | 0.000088 | 0.000904 | kd_tree | 1 | 1 | 0.929 | 0.105632 | 0.002068 | 0.910 | 8.561059 | 8.562700 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.033206 | 0.020860 | NaN | 0.000482 | 0.000033 | kd_tree | -1 | 1 | 0.891 | 0.000454 | 0.000056 | 0.879 | 73.202972 | 73.756421 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.024285 | 0.001525 | NaN | 0.000659 | 0.000024 | kd_tree | -1 | 5 | 0.911 | 0.000712 | 0.000066 | 0.905 | 34.119666 | 34.268086 |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.039488 | 0.008824 | NaN | 0.000405 | 0.000039 | kd_tree | 1 | 100 | 0.894 | 0.005072 | 0.000353 | 0.917 | 7.785052 | 7.803839 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.041841 | 0.007527 | NaN | 0.000382 | 0.000042 | kd_tree | -1 | 100 | 0.894 | 0.005072 | 0.000341 | 0.917 | 8.249540 | 8.268117 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.021844 | 0.002233 | NaN | 0.000732 | 0.000022 | kd_tree | 1 | 5 | 0.911 | 0.000820 | 0.000230 | 0.905 | 26.651468 | 27.684826 |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.021050 | 0.001284 | NaN | 0.000760 | 0.000021 | kd_tree | 1 | 1 | 0.891 | 0.000511 | 0.000274 | 0.879 | 41.208238 | 46.778862 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.358 | 0.129 | 0.024 | 0.0 | -1 | 1 | 0.833 | 0.130 | 4.032 | 4.081 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.924 | 0.171 | 0.020 | 0.0 | -1 | 5 | 0.821 | 0.143 | 4.782 | 4.854 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.863 | 0.168 | 0.021 | 0.0 | 1 | 100 | 0.776 | 0.027 | 4.978 | 4.981 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.790 | 0.154 | 0.021 | 0.0 | -1 | 100 | 0.761 | 0.015 | 4.982 | 4.983 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.797 | 0.108 | 0.021 | 0.0 | 1 | 5 | 0.734 | 0.008 | 5.172 | 5.173 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.804 | 0.053 | 0.021 | 0.0 | 1 | 1 | 0.746 | 0.026 | 5.097 | 5.100 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.014 | 0.0 | -1 | 1 | 0.004 | 0.002 | 0.279 | 0.329 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.024 | 0.0 | -1 | 5 | 0.002 | 0.002 | 0.390 | 0.595 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.530 | 0.581 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.027 | 0.0 | -1 | 100 | 0.001 | 0.001 | 0.532 | 0.584 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.029 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.558 | 0.562 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.024 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.771 | 0.775 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.892 | 1.172 | 0.000 | 0.001 | -1 | 1 | 0.113 | 0.005 | 7.870 | 7.876 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 10.288 | 10.685 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.142 | 0.397 | 0.000 | 0.001 | -1 | 5 | 0.197 | 0.003 | 5.803 | 5.803 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.000 | 0.000 | 8.218 | 8.514 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.498 | 0.533 | 0.000 | 0.005 | 1 | 100 | 0.594 | 0.007 | 9.251 | 9.252 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 3.740 | 3.891 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.022 | 0.291 | 0.000 | 0.003 | -1 | 100 | 0.568 | 0.011 | 5.319 | 5.320 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.002 | 0.000 | 0.006 | -1 | 100 | 0.001 | 0.000 | 7.424 | 7.784 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.672 | 0.246 | 0.000 | 0.002 | 1 | 5 | 0.194 | 0.006 | 8.607 | 8.611 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 3.882 | 4.154 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.904 | 0.194 | 0.000 | 0.001 | 1 | 1 | 0.106 | 0.002 | 8.561 | 8.563 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 3.603 | 3.871 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.033 | 0.021 | 0.000 | 0.000 | -1 | 1 | 0.000 | 0.000 | 73.203 | 73.756 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 31.704 | 32.592 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.002 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 34.120 | 34.268 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 22.681 | 23.367 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.039 | 0.009 | 0.000 | 0.000 | 1 | 100 | 0.005 | 0.000 | 7.785 | 7.804 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 5.350 | 5.531 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.042 | 0.008 | 0.000 | 0.000 | -1 | 100 | 0.005 | 0.000 | 8.250 | 8.268 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 20.554 | 21.261 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.002 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 26.651 | 27.685 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 7.978 | 8.205 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.001 | 0.000 | 41.208 | 46.779 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 6.808 | 7.016 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.568 | 0.089 | 30 | 0.028 | 0.0 | random | 0.470 | 0.043 | 1.208 | 1.213 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.617 | 0.023 | 30 | 0.026 | 0.0 | k-means++ | 0.500 | 0.028 | 1.236 | 1.238 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.927 | 0.253 | 30 | 0.135 | 0.0 | random | 2.795 | 0.031 | 2.120 | 2.120 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.242 | 0.125 | 30 | 0.128 | 0.0 | k-means++ | 2.935 | 0.027 | 2.126 | 2.127 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.010 | 0.000 | random | 0.0 | 0.0 | 8.407 | 13.110 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | random | 0.0 | 0.0 | 8.556 | 12.540 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.010 | 0.000 | k-means++ | 0.0 | 0.0 | 10.844 | 12.057 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 15.926 | 16.614 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.001 | 30 | 0.425 | 0.000 | random | 0.0 | 0.0 | 6.255 | 6.696 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.001 | 0.002 | random | 0.0 | 0.0 | 13.624 | 14.047 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.424 | 0.000 | k-means++ | 0.0 | 0.0 | 6.106 | 6.324 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.001 | 0.002 | k-means++ | 0.0 | 0.0 | 13.173 | 13.837 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 0.001090 | 10000 | 1000 | 2 | 0.002212 | 0.000313 | 20 | 0.007234 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000126 | 0.000646 | 0.000094 | -0.000965 | 3.423656 | 3.459549 |
| 4 | KMeans_short | predict | 0.001995 | 10000 | 1000 | 2 | 0.002235 | 0.000322 | 20 | 0.007160 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.001245 | 0.000506 | 0.000070 | -0.000750 | 4.418226 | 4.459899 |
| 7 | KMeans_short | predict | 0.015034 | 10000 | 1000 | 100 | 0.002749 | 0.000200 | 20 | 0.290985 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.278733 | 0.001099 | 0.000149 | 0.293767 | 2.501037 | 2.523774 |
| 10 | KMeans_short | predict | 0.060044 | 10000 | 1000 | 100 | 0.003040 | 0.000426 | 20 | 0.263146 | 0.000003 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.317011 | 0.001151 | 0.000097 | 0.256968 | 2.642407 | 2.651786 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.088 | 0.002 | 20 | 0.002 | 0.0 | random | 0.033 | 0.002 | 2.694 | 2.701 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.254 | 0.004 | 20 | 0.001 | 0.0 | k-means++ | 0.100 | 0.005 | 2.544 | 2.547 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.228 | 0.005 | 20 | 0.035 | 0.0 | random | 0.127 | 0.002 | 1.797 | 1.797 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.691 | 0.015 | 20 | 0.012 | 0.0 | k-means++ | 0.352 | 0.008 | 1.962 | 1.963 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | random | 0.001 | 0.0 | 3.424 | 3.460 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 14.208 | 14.543 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.0 | 4.418 | 4.460 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 12.309 | 13.268 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.291 | 0.000 | random | 0.001 | 0.0 | 2.501 | 2.524 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 11.056 | 11.241 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.263 | 0.000 | k-means++ | 0.001 | 0.0 | 2.642 | 2.652 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.001 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 11.047 | 11.235 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 0.01 | 1000000 | 1000 | 100 | 0.000412 | 0.000413 | [20] | 1.940387 | 4.122889e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.56 | 0.000837 | 0.001468 | 0.55 | 0.492486 | 0.994060 |
| 4 | LogisticRegression | predict | 0.07 | 1000 | 100 | 10000 | 0.001854 | 0.000168 | [26] | 4.316066 | 1.853540e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.35 | 0.004156 | 0.001500 | 0.28 | 0.446004 | 0.474164 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 11.608 | 0.596 | [20] | 0.069 | 0.000 | 1.922 | 0.019 | 6.038 | 6.039 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.050 | 0.757 | [26] | 0.076 | 0.001 | 0.769 | 0.035 | 1.366 | 1.367 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 1.940 | 0.0 | 0.001 | 0.001 | 0.492 | 0.994 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.010 | 0.0 | 0.000 | 0.000 | 0.528 | 0.535 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 4.316 | 0.0 | 0.004 | 0.001 | 0.446 | 0.474 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 0.727 | 0.0 | 0.001 | 0.000 | 0.163 | 0.164 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | diff_r2_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 0.039624 | 1000 | 1000 | 10000 | 0.010012 | 0.000279 | NaN | 7.990133 | 0.00001 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.082567 | 0.017062 | 0.001144 | 0.122191 | 0.586832 | 0.588149 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.187 | 0.004 | 0.429 | 0.0 | 0.196 | 0.004 | 0.950 | 0.950 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.270 | 0.229 | 0.630 | 0.0 | 0.327 | 0.264 | 3.883 | 4.989 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.01 | 0.0 | 7.990 | 0.0 | 0.017 | 0.001 | 0.587 | 0.588 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.00 | 0.0 | 1.216 | 0.0 | 0.000 | 0.000 | 0.683 | 0.730 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.00 | 0.0 | 5.281 | 0.0 | 0.000 | 0.000 | 0.424 | 0.686 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.00 | 0.0 | 0.015 | 0.0 | 0.000 | 0.000 | 0.531 | 0.562 | See | See |